Sean Miller September 27, 2021 Call volume forecasts are inarguably an essential tool in the successful delivery of customer care excellence. Your program’s forecast is the map that tells you where to go based on where you’ve been. Without it, you’re lost at sea. With it, you’re one significant step closer to delivering an exceptional customer experience.
But customer care volume forecasting typically relies heavily on historic trends. The prior year’s (or quarter’s) volume trends and arrival patterns can, and generally should, inform your projections about what is coming. There may occasionally be an anomaly – be it a season or a month due to unusual, unpredicted circumstances—but typically those anomalies represent a bump in the road of big picture forecasting.
Most of us have never seen an anomaly like the pandemic until now. In the thick of it, we all scaled up or down depending on what was happening to our business and what our customers needed most. But now what? We’re all bored out of our minds by the phrase “new normal,” but we can’t deny that the pandemic has rearranged our maps. The landscape has totally changed—the map tells us where we’ve been, but it no longer provides accuracy regarding the way forward.
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Let’s look at a couple of examples from our outsourced customer care programs. In March 2020, one of our long-term clients, an eComm grocery retailer doing more than 15,000 same-day grocery deliveries, basically became an essential service. With cities under lockdown and every trip to the grocery store involving risk, home delivery of food became a lifeline rather than a convenience. The number of daily orders, the size of orders, and their customer base all increased exponentially, as did the calls, emails, social media mentions, and live chat sessions with questions and concerns about their service. Contact volume reached as high as 300% of forecast, day after day, week after week. When the most intense phase of the first wave passed, volumes receded. As subsequent waves, with accompanying restrictions, came and went, volumes fluctuated accordingly.
Conversely, another client is a global leader in travel insurance. Our team has provided claims opening support and customer service for this client for more than a dozen years operating in a tripod model alongside their inhouse team and a second outsourced team. In March of 2020, they were our third largest client. As the pandemic spread and travel restrictions took over the world, volume plummeted. By spring of 2021, as volume collapsed to almost nil, the work once done by three teams totaling more than 200 agents, was being handled solely by a small inhouse team. As international travel resumes gradually, our team is back in action, albeit at a reduced capacity. At the time of writing, what would normally be peak season is approaching at the same time the fourth wave is swelling.
So, for these clients, like perhaps your own customer care program – the recent past (year-over-year volume data) is not likely going to be an effective guide for the next 12 months even on a rolling three-month basis. Even when we do finally feel comfortable about being truly post-pandemic (let’s all cross our fingers), it doesn’t mean trends will return to pre-pandemic norms. For many businesses, COVID has permanently changed customer behavior and altered B2B environments.
So how should businesses tackle contact center forecasting in the year ahead?
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Forecasting is naturally a collaborative, multi-faceted effort. An outsourcer’s workforce team’s job is to provide predictions to the client who then puts it in the context of their specific business reality. At that point, the modeling comes back to us and we put it into practice – building staffing models. Historic trends are complemented by real-time insight, industry trends, economic markers, business campaigns, and external factors. In short, it’s a complex algorithm that fuels the insights from workforce management experts who apply their own expertise and make informed “reads”.
The reality we find ourselves in now begs the question: how do you do that with a big gap in normal information? Is there any value in the info from non-covid times? We need to begin by looking at those historic trends, both pre-pandemic and mid-pandemic, and asking, what’s relevant to today, and to tomorrow? It’s understanding what is motivating your customers in the way they buy and interact. It’s acquiring deeper knowledge about your industry sector and your business model to identify subtle trends and indicators.
Our recommendation for the forecasting process over the next 12 months is: stay closer than ever with your workforce team, whether they are an outsourced partner or your own internal team. Parse the data together and collaboratively apply your own business projections to the forecast for coming months. Can you access and leverage relevant data inputs from the past 18 months? For example, in consumer retail, you’ll have a solid understanding of the percent of orders that require a contact. Over the past year and a half, has that percentage been getting larger or smaller – or staying the same as your historic trends? Layer that data into your sales team’s quarterly projections (running multiple scenarios based on potential impacts of the fourth wave) and you have a foundation for your forecast.
For our grocery eComm client, for example, they can’t go back and look at business conditions of 2019 because there has been a profound and lasting change in their base business. We can look at the very stable business environment of 2019: our client did 10,000 deliveries per day and X% of orders drove a contact. Today, in the latter half of 2021 daily deliveries top 15K and we have new baseline of orders: contacts. So, we use recent history to look at order drivers and then apply that data to the new business base.
In short: every business has robust data that they are operationalizing. With your workforce team fully invested in your business and fully looped into that operational plan, they can take that operational info and build out from known trends (percent of orders driving contact, for example.) That is essentially, derivative forecasting based on business reality (rather than forecast based primarily on past history) and we overlay that derivative forecast with new business realities.
Ultimately, the reason why forecasting is the key to a successful customer care program is because it gives workforce management a starting point to build out effective staffing plans to deliver on service level commitments that are aligned with your customer experience. Easy access to a quick, efficient, accurate resolution is at the heart of every successful customer service interaction. And business leaders want to maintain optimal profit. Workforce management aims to find the balance between these objectives, and accurate forecasts enable that to happen.
Forecasters and workforce management are simply going to have to take an agile approach, with the understanding that things are still shifting, and customers are still settling into their own new normal.
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